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AFM signal model for dysarthric speech classification using speech biomarkers

Overview of attention for article published in Frontiers in Human Neuroscience, February 2024
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
3 X users

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
5 Mendeley
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Title
AFM signal model for dysarthric speech classification using speech biomarkers
Published in
Frontiers in Human Neuroscience, February 2024
DOI 10.3389/fnhum.2024.1346297
Pubmed ID
Authors

Mulla Shabber, Eratt Parameswaran Sumesh

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 1 20%
Student > Doctoral Student 1 20%
Unknown 3 60%
Readers by discipline Count As %
Environmental Science 1 20%
Computer Science 1 20%
Unknown 3 60%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 March 2024.
All research outputs
#18,177,700
of 26,591,670 outputs
Outputs from Frontiers in Human Neuroscience
#5,680
of 7,864 outputs
Outputs of similar age
#196,511
of 360,075 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#68
of 114 outputs
Altmetric has tracked 26,591,670 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,864 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.3. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 360,075 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 114 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.